Systems for processing digital representations of images are commonly used to process data representing surfaces such as Digital Elevation Models (DEMs). A DEM is a digital map of the elevation of an area on the earth. The data is collected by any well-known means such as LADAR (Laser Detection and Ranging), or by IFSAR (Interferometric Synthetic Aperture Radar) or the like. In operation, the LADAR instrument transmits light to a target. The transmitted light interacts with and is changed by the target. Some of this light is reflected or scattered back to the sensor of the instrument where it is detected, stored, and analyzed. The change in the properties of the light enables certain properties of the target to be determined. The time required for light to travel to the target and back to the LADAR instrument is used to determine the range to the target. IFSAR is used to ingest and process high-resolution elevation data produced through a technique called radar interferometry. As in the case of LADAR, IFSAR produces data useful for extracting DEMs.
Digital elevation models (DEMs) may be represented as a height map through gray scale images wherein the pixel values are actually terrain elevation values. The pixels are also correlated to world space (longitude and latitude), and each pixel represents some variable volume of that space depending on the purpose of the model and land area depicted.
Referring to FIG. 1 there is shown an example of an airborne LADAR system 100. The system comprises a LADAR instrument 102 mounted on an aircraft 104. Below the aircraft is a target area 107 comprising the ground and a canopy formed by trees and other foliage obstructing the view of the ground (earth) from an aerial view. The LADAR instrument 102 emits a plurality of laser light pulses which are directed toward the ground. The LADAR instrument 102 comprises a sensor 103 that detects the reflections/scattering of the pulses. The LADAR instrument 102 provides 3-D data including elevation (Z) versus position (X,Y) information from a single frame. It should be noted, however, that multiple frames of portions of the area from different perspectives are used to generate the composite image. The tree canopy overlying the terrain results in significant obscuration of targets (e.g. vehicle 106) under that tree canopy. The points received by the sensor 103 of instrument 102 from the ground and the target 106 are thus sparse. Hence, a robust system for processing the points is required. Moreover, to be of the most value, an image of the ground wherein the target 106 can be perceived easily must be available quickly.
Extraction of data points generated by LADAR to produce a DEM is known. However, such methods are computationally intensive, and where a large number of data points are processed, run-time applications can be difficult and/or slow. Therefore, there is a need for more efficient methods and systems for production of DEMs using topological data points. In order to be sensitive enough to detect and discern scene content under heavy obscuration (trees, camouflage netting, etc.), the sensor 103 should be able to trigger on single photons.
In many cases the airborne LADAR data collected by the LADAR sensor 103 includes ringing (false images) caused by random events in the electronics of the sensor 103 and stray ambient photons that cause dark noise (false returns) to significantly obscure scene content. Effective filtering is required for registration of LADAR images because registration of images comprising too many noise points provides poor results. An efficient near real-time method is therefore needed to improve signal-to-noise ratio (SNR) by filtering out these false returns.